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We present a unified framework for the construction of localized exponential integrators that bypasses the traditional trade-off between the accuracy of global spectral methods and the efficiency of sparse finite differences. By evaluating…

Numerical Analysis · Mathematics 2026-03-18 Víctor Bayona

In this article, we construct a numerical method for a stochastic version of the Susceptible Infected Susceptible (SIS) epidemic model, expressed by a suitable stochastic differential equation (SDE), by using the semi-discrete method to a…

Numerical Analysis · Mathematics 2023-07-28 Yiannis Kiouvrekis , Ioannis S. Stamatiou

The monomer-dimer model is fundamental in statistical mechanics. However, it is $#P$-complete in computation, even for two dimensional problems. A formulation in matrix permanent for the partition function of the monomer-dimer model is…

Statistical Mechanics · Physics 2009-11-13 Yan Huo , Heng Liang , Si-Qi Liu , Fengshan Bai

Fast and accurate simulation of dynamical systems is a fundamental challenge across scientific and engineering domains. Traditional numerical integrators often face a trade-off between accuracy and computational efficiency, while existing…

Computational Engineering, Finance, and Science · Computer Science 2026-03-06 Jiaxin Yuan , Haizhao Yang , Maria Cameron

Variational integrators are well-suited for simulation of mechanical systems because they preserve mechanical quantities about a system such as momentum, or its change if external forcing is involved, and holonomic constraints. While they…

Optimization and Control · Mathematics 2017-09-04 Elliot Johnson , Jarvis Schultz , Todd Murphey

We consider the approximation of expectations with respect to the distribution of a latent Markov process given noisy measurements. This is known as the smoothing problem and is often approached with particle and Markov chain Monte Carlo…

Computation · Statistics 2019-02-06 Lawrence Middleton , George Deligiannidis , Arnaud Doucet , Pierre E. Jacob

In this paper we consider various splitting schemes for unsteady problems containing the grad-div operator. The fully implicit discretization of such problems would yield at each time step a linear problem that couples all components of the…

Numerical Analysis · Computer Science 2016-11-18 Peter Minev , Petr N. Vabishchevich

Singularly perturbed systems (SPSs) are prevalent in engineering applications, where numerically solving their initial value problems (IVPs) is challenging due to stiffness arising from multiple time scales. Classical explicit methods…

Numerical Analysis · Mathematics 2025-04-15 Yibo Shi , Cristian R. Rojas

The scattering-adapted flexible inner region ensemble separator (SAFIRES) is a partitioning scheme designed to divide a simulation cell into two regions to be treated with different computational methodologies. SAFIRES prevents particles…

Chemical Physics · Physics 2022-03-25 Björn Kirchhoff , Elvar Örn Jónsson , Asmus Ougaard Dohn , Timo Jacob , Hannes Jónsson

When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon…

Computational Physics · Physics 2014-08-08 David A. Sivak , John D. Chodera , Gavin E. Crooks

For many systems of differential equations modeling problems in science and engineering, there are often natural splittings of the right hand side into two parts, one of which is non-stiff or mildly stiff, and the other part is stiff. Such…

Numerical Analysis · Mathematics 2018-11-07 Giuseppe Izzo , Zdzislaw Jackiewicz

Compatible Discrete Operator schemes preserve basic properties of the continuous model at the discrete level. They combine discrete differential operators that discretize exactly topological laws and discrete Hodge operators that…

Numerical Analysis · Mathematics 2014-01-31 Jerome Bonelle , Alexandre Ern

Irregular sampling intervals and missing values in real-world time series data present challenges for conventional methods that assume consistent intervals and complete data. Neural Ordinary Differential Equations (Neural ODEs) offer an…

Machine Learning · Computer Science 2025-01-28 YongKyung Oh , Dong-Young Lim , Sungil Kim

We review and compare numerical methods that simultaneously control temperature while preserving the momentum, a family of particle simulation methods commonly used for the modelling of complex fluids and polymers. The class of methods…

Computational Physics · Physics 2020-02-14 Benedict Leimkuhler , Xiaocheng Shang

We develop a validated numerical procedure for continuation of local stable/unstable manifold patches attached to equilibrium solutions of ordinary differential equations. The procedure has two steps. First we compute an accurate high order…

Dynamical Systems · Mathematics 2017-11-21 William D. Kalies , Shane Kepley , J. D. Mireles James

This paper investigates the equations of motion for a relativistic charged particle in a general magnetic field. By reformulating the dynamics in four-dimensional spacetime and separating the linear and nonlinear parts, we construct an…

Numerical Analysis · Mathematics 2026-03-24 Zhirui Shen , Bin Wang

Smoothed particle hydrodynamics (SPH) has been extensively used to model high and low Reynolds number flows, free surface flows and collapse of dams, study pore-scale flow and dispersion, elasticity, and thermal problems. In different…

Numerical Analysis · Mathematics 2017-12-01 Alexander A. Lukyanov , Kees Vuik

Learning underlying dynamics from data is important and challenging in many real-world scenarios. Incorporating differential equations (DEs) to design continuous networks has drawn much attention recently, however, most prior works make…

Machine Learning · Computer Science 2023-02-03 Yesom Park , Jaemoo Choi , Changyeon Yoon , Chang hoon Song , Myungjoo Kang

We describe a parallel solver for the discretized weakly singular space-time boundary integral equation of the spatially two-dimensional heat equation. The global space-time nature of the system matrices leads to improved parallel…

Numerical Analysis · Mathematics 2021-02-23 Stefan Dohr , Michal Merta , Günther Of , Olaf Steinbach , Jan Zapletal

Efficient and stable solution of partial differential equations (PDEs) is central to scientific and engineering applications, yet existing numerical solvers rely heavily on matrix based discretizations, while learning based methods require…

Machine Learning · Computer Science 2026-04-30 Yi Bing , Zheng Ran , Fu Jinyang , Liu Long , Peng Xiang